Sentence Similarity
Safetensors
sentence-transformers
Turkish
PyLate
modernbert
ColBERT
feature-extraction
Generated from Trainer
dataset_size:910904
loss:Contrastive
text-embeddings-inference
Instructions to use newmindai/ColmmBERT-base-TR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use newmindai/ColmmBERT-base-TR with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="newmindai/ColmmBERT-base-TR") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Local Installation Video and Testing - Step by Step
#1
by fahdmirzac - opened
Hi,
Kudos on producing such a sublime model. I did a local installation and testing video :
https://youtu.be/bZamvZojMA0?si=bHZ5p6M3t9FKXZqh
Thanks and regards,
Fahd
Hi Fahd,
Thank you so much for the kind words about the model! We are incredibly grateful for your contribution. Your tutorial video is excellent, so we have featured it directly on our GitHub page (https://github.com/ozayezerceli/TurkColBERT) to help others with local installation and testing.
Thanks again for the support!
Best regards,
Özay Ezerceli
New Mind AI Research Team